From Cards to Code: Coding a Prototype with ChatGPT
I’ve always loved tabletop games—and a while back, I designed one myself. A turn-based monster hunting card game, full of asymmetric rules, layered interactions, and tactical gameplay. But I wanted to see if I could bring it to life beyond the tabletop.
The only catch? I don’t code.
So I asked ChatGPT: “How would I go about simulating a card-based tabletop game using Python?”
That kicked off an iterative process where I:
Described my game’s basic structure and mechanics
Defined player roles, card interactions, and turn logic
Asked for modular Python functions to simulate game flow
The result? A functioning game simulation in Python that successfully runs about 80% of the game’s core rules. No UI yet. No fancy graphics. But a working logic engine that replicates most of the turn-by-turn mechanics of the physical version.
What I Learned
This wasn’t just an experiment in code—it was an experiment in how AI can translate ideas into structure. I used ChatGPT like a coding coach, asking questions like:
“How should I structure a deck and hand system?”
“What’s the best way to randomize monster behavior?”
“How can I track player health and abilities across turns?”
It helped me debug errors, rethink the logic of certain rules, and see how my game systems could be improved through simulation.
What’s Next
Add player interaction (so it’s not just a simulation, but a playable experience)
Finalize the last 20% of rules, including complex abilities and edge cases
Eventually, create a basic UI—or even port the logic to Tabletop Simulator
This project showed me that even without a technical background, tools like ChatGPT make it possible to prototype ideas, test systems, and actually build things—one prompt at a time.
Whether you’re a marketer, a parent, or a game designer, the takeaway is simple: you don’t have to be a coder to start building. You just need a little curiosity and the right AI co-pilot.
